Hearing aid having an adaptive classifier

ABSTRACT

A hearing system includes a hearing aid (10) and personal communication device (20) connected via a short range data communication link. The hearing aid has a signal processor (13) processing an audio signal according to audio processing parameters, a sub-system applying respective sets of processing parameters for at least two modes, a classifier component (51) statistically analyzing the environment by comparing specific characteristics of an electrical input signal to one or more thresholds. A program selector component (16) selects automatically an appropriate mode for the signal processing sub-system according to the classifier output. The personal communication device offers the user an interface for controlling and interacting with the program selector component of the hearing aid, and for generating and transmitting a notification to the hearing aid. Upon reception of the notification, the processor adjusts at least one of the one or more thresholds used by the classifier component.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.15/810,527 filed Nov. 13, 2017, which is a divisional of U.S.application Ser. No. 15/047,706 filed Feb. 19, 2016, now U.S. Pat. No.9,883,297, which is a continuation-in-part of application No.PCT/EP2013/067272 filed on Aug. 20, 2013, and published as WO2015024585A1, the disclosures of all of which are incorporated herein by referencein their entirety.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to hearing aids. The invention, moreparticularly, relates to a hearing system having a classifierclassifying an auditory environment and selecting a mode of operationfor one or more signal processing sub-systems each having at least twomodes of operation. The hearing system includes a hearing aid and apersonal communication device. Also, the invention relates to a methodof controlling program selection in a hearing aid.

2. Prior Art

Basically, a hearing aid has a microphone for converting sound into anelectric signal, and an amplifier for alleviating the hearing loss ofthe user and a receiver for converting the amplified electric signalinto sound again. Modern, digital hearing aids comprise sophisticatedand complex signal processing units for processing and amplifying soundaccording to a prescription aimed at alleviating a hearing loss for ahearing impaired individual. The major purpose of a hearing aid is toimprove speech intelligibility. State of the art hearing aids havefeatures for recognizing speech and suppressing noise in an audio signalpicked up by the hearing aid. A useful element in the statisticalanalyses is percentile levels. Percentile levels provide information onthe level distribution, that is, how the loudness level of the incomingsignal changes over time. When obtained for multiple frequencies, thisinformation provides quite a detailed picture of the auditoryenvironment. U.S. Pat. Nos. 7,804,974 B and 8,411,888 B describe theoperation of a hearing aid classifier in details.

The purpose of the invention is to provide an improved classifier forprogram selection in a hearing aid wherein the risk of undesired programchanges is minimized.

SUMMARY OF THE INVENTION

This purpose is achieved by a hearing system according to the inventionincluding a hearing aid and a personal communication device. Accordingto a first aspect of the invention there is provided a hearing systemincluding a hearing aid and a personal communication device bothincluding a short range data transceiver for providing a short rangedata communication link. The hearing aid includes a signal processorprocessing an electric input signal according to audio processingparameters of the hearing aid, and a classifier component analyzing atleast one specific characteristic of said electric input signalstatistically, said statistical analysis includes comparison of said atleast one specific characteristic to one or more thresholds. A programselector component automatically selects one of at least two modes ofoperation for a signal processing sub-system according to theclassifier's classification. The thresholds are controlled by the signalprocessor. The personal communication device offers the user a userinterface for controlling and interacting with a program selectorcomponent of the hearing aid, and generating a notification according tothe operation of the user interface and transmitting the notification tosaid hearing aid via said short range data communication link. Uponreception of the notification from said personal communication device,the processor adjusts at least one of said one or more thresholds usedby the classifier component.

According to a second aspect of the invention there is provided a methodof selecting one of at least two modes of operation for a signalprocessing sub-system for a hearing aid including a signal processorprocessing an electric input signal according to audio processingparameters of the hearing aid. The method includes connecting a personalcommunication device to the hearing aid by means of a short range datacommunication link, analyzing in a classifier at least one specificcharacteristic of said electric input signal statistically in order todetermine the acoustic environment of the hearing aid, said statisticalanalysis including comparison of at least one specific to one or morethresholds, and offering the user by means of said personalcommunication device a user interface for controlling and interactingwith a program selector component of the hearing aid. The methodfurthermore includes steps of generating a notification according to theoperation of the user interface and transmitting the notification tosaid hearing aid via said short range data communication link, andadjusting at least one of said one or more thresholds used by theclassifier component upon reception of the notification from saidpersonal communication device.

According to a third aspect of the invention there is provided a hearingaid communicating with the personal communication device via a shortrange data communication link. The hearing aid includes a signalprocessor processing an electric input signal according to audioprocessing parameters of the hearing aid, a classifier componentanalyzing at least one specific characteristic of said electric inputsignal statistically, said statistical analysis including comparison ofat least one specific characteristic to one or more thresholds, and aprogram selector component automatically selecting one of at least twomodes of operation for a signal processing sub-system according to saidstatistical analysis performed by the classifier component. The signalprocessor is adapted to receive a notification from said personalcommunication device and initiated by a user operating a user interfaceallowing the user to control said program selector component, and toadjust the thresholds of the classifier component upon reception of thenotification from said personal communication device.

According to a fourth aspect of the invention there is provided ahearing aid including a signal processor processing an electric inputsignal according to audio processing parameters of the hearing aid, afeature extractor for extracting value representations relating to atleast one specific characteristic for said samples of said electricinput signal, and a classifier component analyzing said valuerepresentations statistically by comparing said value representations toone or more thresholds for said at least one specific characteristic.The signal processor furthermore analyzes the statistical distributionof said value representations for evaluating the homogeneity of theauditory environment. When the signal processor recognizes the auditoryenvironment as being homogeneous, the signal processor compares the meanvalue of the distribution to the threshold for said at least onespecific characteristic. When the signal processor recognizes thedifference between the mean value and one of said one or more thresholdsto be below a first predetermined value, the signal processor adjust thethresholds so said difference at least corresponds to said firstpredetermined value.

According to a fifth aspect of the invention there is provided a methodof classifying an acoustic environment for a hearing aid including asignal processor processing an electric input signal according to audioprocessing parameters of the hearing aid. The method includes extractingin a feature extractor value representations relating to at least onespecific characteristic for said samples of said electric input signal,analyzing in a classifier component said value representationsstatistically by comparing said value representations to one or morethresholds for said at least one specific characteristic, and analyzingin the signal processor the statistical distribution of said valuerepresentations for evaluating the homogeneity of the auditoryenvironment. When the signal processor has recognized the auditoryenvironment as being homogeneous, the signal processor furthermorecompares the mean value of the distribution to said one or morethresholds for said at least one specific characteristic, and when thesignal processor has recognized that the difference between the meanvalue and one of said one or more thresholds is below a firstpredetermined value, the signal processor adjusts one of said one ormore thresholds so said difference at least corresponds to said firstpredetermined value.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described in further detail with reference topreferred aspects and the accompanying drawing, in which:

FIG. 1 illustrates schematically a hearing aid system according to anembodiment of the invention;

FIG. 2 shows four categories of an audio signal observed in a hearingaid—illustrated as amplitude versus time;

FIG. 3 illustrates program selection according to the first aspect ofthe invention;

FIG. 4 illustrates a method of selecting programs in a hearing aidaccording to a first aspect of the invention;

FIG. 5 illustrates the user interface for application software forcontrolling a hearing aid and serving as an auxiliary classifieraccording to an embodiment of the invention;

FIG. 6 illustrates possible decisions made by a first embodiment of theclassifier and the auxiliary classifier according to the invention;

FIG. 7 shows a flow chart for a method according to an embodiment of theinvention for changing program for a sub-system and modifying thresholdsadaptively;

FIG. 8 illustrates the distribution for a specific characteristic audiosamples of an auditory environment being substantially homogeneous; and

FIG. 9 illustrates a two-dimensional feature space for an adaptiveclassifier according to an embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Reference is made to FIG. 1, which schematically illustrates a hearingsystem according to an embodiment of the invention. Prior to use, thesettings of the hearing aid is set and adjusted by a hearing careprofessional according to a prescription. The prescription is providedby an audiologist and is based on a hearing test, resulting in aso-called audiogram, of the performance of the hearing-impaired user'sunaided hearing. The prescription is developed to reach a setting wherethe hearing aid will alleviate a hearing loss by amplifying sound atfrequencies in those parts of the audible frequency range where the usersuffers a hearing deficit.

A hearing aid 10 comprises two input transducers 11, 12 for picking upthe acoustic sound and converting it into electric signals. The electricsignals from the two transducers 11, 12 are led to a Digital SignalProcessing (DSP) unit 13 for amplification and conditioning according toa predetermined setting set by an audiologist. An advantage of having adual microphone system is that it makes it possible to perform spatialfiltering. The input signal is preferably split into a number of narrowfrequency bands which can then be processed separately. The DigitalSignal Processing (DSP) unit 13 delivers an amplified and conditionedelectrical output signal to a speaker or an output transducer 14.Preferably Delta-Sigma-conversion is applied in the signal processing sothe electrical output signal is formed as a one-bit digital data streamfed directly to the output transducer 14, whereby the hearing aid 10drives the output transducer 14 as a class D amplifier.

The hearing aid 10 includes a standard hearing aid battery (not shown)as power supply and may in addition also include a tele-coil (not shown)for picking up a broadcasted electromagnetic signal.

The Digital Signal Processing (DSP) unit 13 includes an automaticprogram selector component 16 that analyzes the incoming audio signaland selects the hearing aid program accordingly or adjusts the settingthereof which is indicated by a control signal 17. Furthermore, thehearing aid 10 includes a connectivity component 15 for communicationwith a personal communication device 20. The connectivity component 15operates preferably according to the Bluetooth Core Specificationversion 4.0—also known as Bluetooth Low Energy. Such connectivitycomponents 15 are commercially available as a dedicated chip fromvarious manufacturers, and by including such a component into a hearingaid, it becomes possible to connect the hearing aid to the Internet viaa connection to a smartphone, a tablet computer or other types ofexternal communication devices and to get the benefits from such aconnection.

The personal communication device 20 may access an external server 40via the Internet 35, and download a piece of application software (app)dedicated for the hearing aid 10. When run on the personal communicationdevice 20, the application software according to the invention providesa functionality of an external auxiliary classifier 24. The classifier16 analyzes the auditory environment, while the external auxiliaryclassifier 24 analyzes the user position and behavior, and may alsoretrieve information about acoustic characteristics of the surroundings.The auxiliary classifier 24 may extract the position data of thepersonal communication device 20 as these data are available from theprocessor 23.

The personal communication device 20 may include an electronic calendarand a clock. Most people do have some daily routines, which are repeatedweek after week. Most people work five days a week—often from nine tofive.

According to the invention, the personal communication device 20includes a connectivity component 29 that may communicate with thehearing aid 10 and therefor preferably operates under the Bluetooth CoreSpecification, version 4.0.

The personal communication device 20 includes a User Interface (UI) 27,such as a touch display, presenting content, input screens, andnotifications to the user and allowing the user to input instructionsand commands. An NFC reader 28 allows the personal communication device20 to interact with an NFC tag 34 or unit for reading the codeassociated therewith.

The personal communication device 20 may be a mobile phone having amicrophone 21, a speaker 22, and a processor 23 controlling theoperation. The personal communication device 20 is intended to providethe user a wide variety of communication services, and for this purposethe personal communication device 20 includes a wireless transceiver,such as a Radio Frequency (RF) component 25 and a corresponding antennamodule 26.

The RF component 25 is controlled by the system software run on theprocessor 23 and includes a cellular part 31 for communication (mobilephone calls and data connection) over a cellular network using cellularprotocols such as GSM (2G), WCDMA (3G) and/or LTE (4G)—whereby thepersonal communication device 20 is able to connect to the Internet 35.When accessing a cellular network, the personal communication device 20links up to a base station in the cellular network. This base station isnamed by the network operator, and the name or the Cell-ID is agenerally unique number used to identify each Base Transceiver Station(BTS), and is a rough indication of the current location of the personalcommunication device 20. The processor 23 keeps track on available basestations, the one to which the personal communication device 20 iscurrently connected, and manages hand-overs when required.

Even through there is a significant uncertainty when using the Cell-IDfor exact determination of a position, the telephone may know anadditional parameter named Timing Advance which represent a measure forthe distance to the Base Transceiver Station, and by keeping track ofthe telephones Base Transceiver Station history, the auxiliaryclassifier 24 may easily recognize a pattern as most people have fixedroutine in commuting between home and work and in addition to this doinga little sport and shopping. These details may be flagged in thecalendar so the app controlling the auxiliary classifier 24 may retrievethe details including category and timing directly from the calendar.

The RF component 25 may furthermore include a WLAN modem 32 preferablyoperating according to the IEEE 802.11 protocol (including one or moreof the standards 802.11a, 802.11g and 802.11n). Hereby the personalcommunication device 20 is able to connect to the Internet 35 via arouter 30 when permitted to access the WLAN network. When the WLAN modem32 is switched on, the processor 23 maintains a list of available WLANnetworks, and this knowledge can be used to determine whether thepersonal communication device 20 is at home, at work or at some otherposition previously defined by the WLAN network access. The processor 23manages the handshaking when a permitted WLAN network is accessible. Theprocessor 23 may also manage a list of all available WLAN networks inthe surroundings—not only the one to which the personal communicationdevice 20 is connected.

The RF component 25 may furthermore include a GPS receiver 33 receivingsatellite signals, and based on the signals calculating a representationfor the current position of the personal communication device 20. Thisrepresentation or coordinates may be used for navigation, but isactually also a quite precise indication of the current position of thepersonal communication device 20. When GPS receiver 33 is switched onthe processor 23 often uses the coordinates for presenting the currentposition on a displayed map. Most GPS apps are able to extract thecurrent speed of the personal communication device 20, and this may beused as an indication of the current use—and indicate travelling e.g. bycar or train. The external auxiliary classifier 24 may disregard the GPSreceiver 33 as information source, when the GPS receiver 33 is turnedoff for power saving reasons.

Furthermore the connectivity component 29 (Bluetooth module) may be usedin various situations—for example for connecting the personalcommunication device 20 to a hands-free system of a car. Bluetoothhands-free options are today easily found in mid and high-end cars as anintegrated part of the cars stereo system. The system software of theprocessor 23 manages the hands-free profile, and such a hands-freeprofile has been standardized as “SIM ACCESS PROFILE InteroperabilitySpecification” by the Bluetooth® Special Interest Group (SIG), Inc.

During the past decade, one of the strategies to improve the hearingskills of a hearing impaired person has been to analyze the auditoryenvironment of the hearing aid user in order to identify useful soundcomponents and noise, and using this knowledge to remove the identifiednoise from the audio signal presented to the hearing aid user. Thissignal analysis and subsequent classification of the audio signal pickedup may include simultaneously examination of three specificcharacteristics inherent in the analyzed signals. The first specificcharacteristic may be the Intensity Change. The Intensity Change isdefined as the change in the intensity of the audio signal over amonitored time period. The second specific characteristic may be theModulation Frequency. The Modulation Frequency is defined as the rate atwhich the signal's intensity changes over a monitored time period. Thethird specific characteristic may be the Time. The Time is simplydefined as the duration of the signal.

FIG. 2 shows four categories of audio signal that may be observed in ahearing aid—illustrated as amplitude versus time.

The first audio signal example labeled “a) Stationary noise”, ischaracterized in that it is stable during the analyzing period of e.g. acouple of seconds. Furthermore the intensity does not change and thesignal is not modulated—in other words the spectral composition remainsthe same during the analyzing period. The typical source for stationarynoise includes an air conditioner or an engine.

The second audio signal example is labeled “b) Pseudo-stationary noise”,and it is characterized in that it is substantially stable during theanalyzing period—even though modulation may be observed. The typicalsource for pseudo-stationary noise includes traffic noise and a crowd ofpeople splitting into smaller groups having individual conversations(cocktail party).

The third audio signal example is labeled “c) Speech”. Speech ischaracterized in that it is heavily modulated with silent parts inbetween. If analyzing the frequency domain in addition, it may be seenthat the individual sounds vary in frequency, too.

The fourth audio signal example is labeled “d) Transient noise”. Thetypical source for transient noise may be door-slamming, shooting orhammering. Common for transient noise is that the noise is extremelyuncomfortable when amplified and output directly in the ear. Thetransient noise is not used for automatically program selection but thehearing aid, upon detection of such a sound, seeks to cancel out thesound without amplifying it.

The continuum between audio signal examples and the specificcharacteristics are listed in Table 1 below.

TABLE 1 illustrates the correlation between specific characteristics ofaudio signal and origin of the received audio signal. Pseudo- Tran-Station- station- sient ary noise ary noise Speech noise Intensity Small<--------------------------------------------> Significant ChangeModulation low <------------------------------------------------------->high Frequency Duration of stable<-------------------------------------------------------> short thesignal (time)

Now referring to FIG. 6, the three specific characteristics parameters“Intensity change”, “Modulation”, and “Duration” is shown. For“Intensity change”, the dynamic range is divided into three intervals,I1, I2 and I3, by providing two thresholds, “Threshold I1” and“Threshold I2”. Similar to this the “Modulation” divided into twointervals, M1 and M2, by means of a threshold, “Threshold M1”, and the“Duration” is divided into two intervals, D1 and D2, by means of athreshold, “Threshold D1”. From the external auxiliary classifier 24,the programs selector 16 receives location input—here marked as “Home”,“Office”, “Car” and “Elsewhere”.

Hereby you are able to associate the specific characteristics parameterintervals into bins, and handle the bins as a histogram so the mostsignificant bin is used by the program selector 16 for automaticselection of the hearing aid program best fitting the auditoryenvironment and user behavior. For example when driving in a car, thecar engine has a characteristic noise pattern that may be suppressed asit does not add any valuable information to the user if amplified.

TABLE 2 illustrates how noise landscapes and position information may beput together in a histogram used for program selection. IntensityModulation Dura- Bin Change Frequency tion Location 1 I1 M1 D1 Home 2 I1M1 D1 Office 3 I1 M1 D1 Car 4 I1 M1 D1 Elsewhere 5 I1 M1 D2 Home 6 I1 M1D2 Office 7 I1 M1 D2 Car 8 I1 M1 D2 Elsewhere 9 I1 M2 D1 Home 10 I1 M2D1 Office 11 I1 M2 D1 Car 12 I1 M2 D1 Elsewhere 13 I1 M2 D2 Home 14 I1M2 D2 Office 15 I1 M2 D2 Car 16 I1 M2 D2 Elsewhere 17 I2 M1 D1 Home 18I2 M1 D1 Office 19 I2 M1 D1 Car 20 I2 M1 D1 Elsewhere 21 I2 M1 D2 Home22 I2 M1 D2 Office 23 I2 M1 D2 Car 24 I2 M1 D2 Elsewhere 25 I2 M2 D1Home 26 I2 M2 D1 Office 27 I2 M2 D1 Car 28 I2 M2 D1 Elsewhere 29 I2 M2D2 Home 30 I2 M2 D2 Office 31 I2 M2 D2 Car 32 I2 M2 D2 Elsewhere 33 I3M1 D1 Home 34 I3 M1 D1 Office 35 I3 M1 D1 Car 36 I3 M1 D1 Elsewhere 37I3 M1 D2 Home 38 I3 M1 D2 Office 39 I3 M1 D2 Car 40 I3 M1 D2 Elsewhere41 I3 M2 D1 Home 42 I3 M2 D1 Office 43 I3 M2 D1 Car 44 I3 M2 D1Elsewhere 45 I3 M2 D2 Home 46 I3 M2 D2 Office 47 I3 M2 D2 Car 48 I3 M2D2 Elsewhere

With reference to FIG. 3, the operation of the programs selector 16 willbe discussed. The transducers 11, 12 receive sound from a plurality ofsound sources #1, #2, . . . , #N. The program selector 16 includes afeature extractor 50 being adapted to analyze an audio signal sample bydetermining characteristic parameters as the “Intensity Change”, the“Modulation Frequency” and the “Duration” of the signal. Theseparameters are handed over to a classifier 51 being adapted to classifythe audio signal sample by comparing the determined characteristicparameters with some predetermined threshold values. The classifier 51updates a histogram by incrementing the appropriate bin by one.

An analyzer 52 monitors the histogram and identifies the dominant bin torepresent the current noise landscape, and the analyzer 52 instructs theDSP 13 to select the corresponding program accordingly. The analyzer 52outputs a command to the DSP 13 to select a program and/or set programsparameters according to current noise landscape. The analyzer 52 mayfurther adjust the time between subsequent noise samples fed to theclassifier 51 in dependence of the histogram whereby a surrounding noiselandscape is monitored more intensively when the landscape isinhomogeneous (no dominant bin in the histogram). In order to makechanges in the auditory environment detectable, exponential forgettinghas been implemented in order to ensure that new auditory samples fed tothe classifier are weighted higher than older samples.

The Digital Signal Processing (DSP) unit 13 includes a plurality ofalgorithms for manipulating the input signals prior to presenting theprocessed signal for the user. These algorithms may be regarded assub-systems as their behavior may be varied by changing settings for thealgorithm.

When the auxiliary classifier 24 detects a change, the processor 23initiates the transmission of an update notification to the hearing aid10. The update notification is prepared as a data package with a header(supplemental data placed at the beginning of a block of data beingtransmitted). It is important that header composition follows a clearand unambiguous specification or format, to allow for parsing. The datapackage is transmitted from the connectivity component 29 to theconnectivity component 15. Based on the header, the update notificationis led to the analyzer 52 which takes this additional information intoaccount when selecting a program or a sub-system.

One example on such a sub-system may be a directional microphone system.One such program or sub-system available from Widex A/Sunder the name HDLocator™ consists of two omnidirectional microphones 11, 12. Themicrophone system is adaptive, meaning that it will assume the polarpattern that produces the best signal-to-noise ratio in the currentlistening environment. In other words, noise is suppressed by employinginput dependent directional patterns.

In a quiet environment with limited noise, the microphone system willassume the omnidirectional pattern where it picks up sound evenly fromall directions. However, if noise is present, the system will assume thedirectional pattern which leads to the least amount of noise beingpicked up. If the noise source is located behind the hearing aid user,for instance, the microphone system will assume a cardioid pattern whichpicks up sound from the front and eliminates most sound from the sidesand from the behind.

This means the adaptive directional pattern can operate in severalindependent frequency bands that the directional pattern assumed tosuppress the noise can be limited very narrowly to the frequency areaswhere the noise is actually present. If a low frequency noise source(e.g. the engine of a car) is located in one direction and a highfrequency noise source (e.g. an espresso machine) in another, a dualmicrophone system can reduce the sensitivity to both sources of noiseindependently, effectively reducing the total amount of noise thathearing aid user will hear.

Another example on such a sub-system may be a transposing system. Theloss of audibility of high frequency sounds often compromises speechunderstanding and the appreciation of music and nature's sounds. Atransposing program or sub-system is available from Widex A/Sunder thename Audibility Extender™. This sub-system transforms inaudible sounds,such as high-frequency speech sounds, and environmental sounds likebirdsong, a doorbell, music, etc. to a frequency region where they areaudible. This preferably takes place by employing a linear frequencytransposition, whereby the important harmonic relationship of sound isretained. This is important for the user experience of specific soundsfor the hearing aid wearer.

The transposing sub-system is essential for assisting the user toimprove the speech perception as phonemes such as /s/, /∫/, /t/, /z/ aredifficult to discriminate if you have a hearing loss in the highfrequencies. In spoken English being able to discriminate /s/ and /z/ isimportant because these phonemes mark plurals, possessions andcontractions as well as the third person singular tense.

A third example on such a sub-system may be a feedback cancellationsub-system. Feedback occurs because the amplified sound from the hearingaid is picked up at the hearing aid microphone and allowed to passthrough the hearing aid again, eventually resulting in the high-frequentwhistling sound. The feedback cancelling system analyzes the incomingsignal, and in case the signal is found to be audible feedbackwhistling, gain will be reduced at the affected frequency to provide astable sound without feedback whistling. When listening to music,feedback cancellation shall be reduced as e.g. the sound of strings maybe interpreted as an audible feedback whistling and therefor cancelledunintentionally.

Room Reverberation Characteristics

Understanding speech in noisy conditions is usually a primary objectivefor hearing aid users. In certain reverberant environments, such aschurches, auditoriums, theaters, the speech audibility for hearing aidusers is very challenging. Reverberation is caused by multi-pathpropagation of the audio signal where the audio signal received by thelistener is composed by the direct propagated signal and one or morereflected contributions (multi-path propagation). The human brain isable to extract information about the room from the heard sound due tothe reverberation. For hearing aid users, the reverberation causes anoisy audio environment, and therefor some binaural hearing aids havealgorithms seeking to remove contribution from reflected signal paths.If the theatre or concert hall is not equipped with appropriate acousticpanels, unwanted sound reflections are produced. This increasesreverberations that make it difficult for the audience to hear thedialogue or music clearly. The challenges of hearing aids in reverberantenvironments have been discussed in “Simulated Reverberation and HearingAids” by M. Izel et al, presented at the American Academy of AudiologyNational Convention 1996, Salt Lake City, Utah.

The multi-path signals depend on size of the room and the surfaces usedin the walls, the floor and the ceiling. The size of the room determinesthe delay of the echoes, and the surfaces determine the relationshipbetween the absorbed and reflected energy—and thereby the relationshipbetween the direct signal and the echoes. The delay value for a room maybe estimated by using a formula called RT60. The first early reflectionreaches the listener shortly after the direct signal does as the path islonger. The difference in time between the arrival of the direct signaland the first early reflections is measured in milliseconds. Currentlyde-reverberation takes place by estimating the room reverberationcharacteristics by analyzing the received audio signal, and thenapplying various filters in the hearing aid for suppressing the echoes.

Preferably, the operators of such reverberant environments, such aschurches, auditoriums, theaters, may as a service make the roomreverberation characteristics for the major rooms or halls available forthe hearing impaired users. One way of making these data available forthe users or customers is by embedding the data into an NFC tag 34 (FIG.1). By printing appropriate icons or descriptive text on the NFC tag 34,the user will be able to obtain the room reverberation characteristicsby means of his NFC enabled personal communication device 20. The dataembedded into the NFC tag 34 includes a header informing the processor23 how data shall be handled when parsed. Thereafter the auxiliaryclassifier 24 extracts the relevant parameters and transfers theseparameters to the programs selector 16 of the hearing aid where theappropriate program is selected and the parameters for thede-reverberation are based on the room reverberation characteristicsachieved by means of the personal communication device 20.

Alternatively, the room reverberation characteristics may be accessedvia a Location Based Service. The application software running on thepersonal communication device 20 retrieves the room reverberationcharacteristics from a memory 41 of the remote server 40. This may bedone by up-loading the current position of the personal communicationdevice 20 to the remote server 40, and the remote server 40 will providethe room reverberation characteristics in response.

According to yet an alternative embodiment, the personal communicationdevice 20 may acquire the URL of the desired room reverberationcharacteristics from the NFC tag 34, and then access the desired datavia the Internet 35. The operators of reverberant environments may as aservice make the room reverberation characteristics available for thehearing impaired users on the server 40 via the Internet 35. Once theroom reverberation characteristics have been acquired by the auxiliaryclassifier 24, the control of the hearing aid 10 upon downloading theroom reverberation characteristics is basically the same as if the roomreverberation characteristics were acquired from the NFC tag 34.

Instead of having a separate service for the room reverberationcharacteristics, the data can be included in an Augmented-Reality-likeservice where artificial information about the environment and itsobjects may be overlaid on the real world camera view. The roomreverberation characteristics data may be handled as a kind of VirtualGraffiti and shall include an identifier to enable the personalcommunication device 20 to direct the data towards the auxiliaryclassifier 24. Virtual Graffiti consists of virtual digital messagesprovided and maintained by individuals. The Virtual Graffitiapplications utilize Augmented or Virtual Reality and UbiquitousComputing to anchor a message to a physical landmark in the real world.Now again, once the room reverberation characteristics have beenextracted by the auxiliary classifier 24, the control of the hearing aid10 is basically the same as if the room reverberation characteristicswere acquired from the NFC tag 34.

The hearing aid 10 according to the invention is able to receive andhandle one or more externally defined classifier categories, and thepersonal device 20 is able to classify the current use into theseexternally defined classifier categories, and offer these categories tothe hearing aid 10. If the personal device 20 and the hearing aid 10become disconnected, the programs selection of the hearing aid 10 ishandled just under control of the classifier 51.

Once the appropriate software application has been downloaded andinstalled, the user may pair the personal device 20 and the hearing aid10. This may be done by switching on the hearing aid 10, which willenable Bluetooth for a predetermined period. This period may be fiveminutes or shorter. Advantageously this period may be just one minute,but extended to e.g. two minutes if the hearing aid 10 detects aBluetooth enabled device in its vicinity. During this period, thehearing aid will search for Bluetooth enabled devices, and when one isfound, the hearing aid may play back a security code in audio, in orderthat the user can key in the security code on the personal device 20.The connection is established and the personal device 20 may from now oncommunicate with the hearing aid 10.

Once the hearing aid app having a user interface 120 (Touch screen shownon FIG. 5 with an apps name area 121) is operating according to theinvention, the user may at step 100 in FIG. 4 start to define his basiclocations. This is done by means of the application software forcontrolling a hearing aid, where the user may press a “NEW” virtual keyin a mode section 122. Then the user is invited to enter a mode label ina per se known manner by means of a virtual keypad (not shown). Examplesof useful, user defined Behavior Modes appear from Table 3. Once aBehavior Mode is defined, the personal device 20 lists in step 102 anycontrol input, as Cell-ID, WLAN connection, being available, and as longas these control inputs are available, the auxiliary classifier 24assumes—in step 104—that the personal device 20 remains in this locationand thereby in this mode. The user sets up all the Behavior Modes hewants to define one by one when he is present in the appropriatelocation. When the auxiliary classifier 24 detects a change in theenvironment in step 106, it checks in step 108 whether the newenvironment is known or not. The auxiliary classifier 24 operates with amode named “Unknown” which is used if none of the predefined modes isdetected. When a mode change is detected, the mode change and the newmode is communicated in step 110 to the hearing aid 10, and theauxiliary classifier 24 continues monitoring the use of the personaldevice 20 at step 104.

The user interface 120 of the personal device 20 offers the user in themode section 122 the opportunity to manually set the mode to one of thepreviously set modes, which is done by pressing the “Change” button,which preferably will offer the user a selector list to choose from. Thehearing aid 10 communicates via the short range data communication linkto personal device 20 which program is currently selected by the programselector 16. The user may via a program selection section 123 change thecurrently selected program by pressing the “Change” button whichpreferably will offer the user a selector list to choose from. Thisselector list preferably offers the user a possibility to maintain theselected program by doing some fine tuning. Via a streaming sourcesection 124, the user may activate and change the streaming source bypressing the “Activate” button and the “Change” button, respectively.Pressing the “Change” button will offer the user a selector list tochoose from. The personal device 20 may manage the streaming fromtelevision, FM radio or telephone. Finally a menu control section 125allows the user access to the entire app menu and to escape the app.

TABLE 3 illustrates which inputs to the auxiliary classifier can be usedto define the current Behavior Modes. Behavior Mode Indicator Home Time,Cell-ID, WLAN Router name Car Bluetooth connection, GPS (speed)Office/Work Time, Cell-ID, WLAN Router name Church Time, Cell-IDFavorite restaurant Time, Cell-ID, WLAN Router name Concert hall,Auditorium, Calendar, NFC tag/“Virtual Graffiti”, theatre, cinema GPSlocation

FIG. 7 illustrates a method according to the invention, and, accordingto this method, the program selector 16 monitors the auditoryenvironment in step 60 by analyzing samples—preferably of apredetermined duration—and classifying the individual sample based uponits specific characteristics. The statistical analysis of the classifier51 includes comparison of the individual samples to one or morethresholds for each of the specific characteristics as seen in FIG. 6,and, in dependence of the comparison incrementing the value of theappropriate bin in the histogram shown in FIG. 3. When the analyzer 52in step 61 detects a change in the histogram (a new bin peaks), itinvestigates whether the new classification is associated with a programdifferent from the one currently used, and if this is the case, theprogram selector 16 automatically changes the program in step 63. Afteridentifying the new peaking bin in step 61, evaluating the need forchanging program in step 62, and changing program in step 63 ifrequired, the program selector 16 goes back to step 60 monitoring theauditory environment for detecting the next change in the auditoryenvironment or in the user behavior.

In parallel to the monitoring of the auditory environment and the userbehavior, the program selector 16 also monitors the user interaction instep 64. This user interaction refers to the user interface 120 shown inFIG. 5 for application software run on the personal communication device20 according to an embodiment of the invention. The inputs arecommunicated from the personal communication device 20 to the hearingaid 10 via the short range data connection provided by the twoconnectivity components 15, 29—the Bluetooth™ transceivers. By pressingthe “Change” button in the program selection section 123, the user willaccording to the preferred embodiment be offered a selector list tochoose from. This selector list preferably offers the user a possibilityto undo a program change recently (e.g. within the last minute)initiated by the program selector 20, and also to do some fine-tuning byindicating that more or less bass or treble is desired, that wind noiseis problematical, or that a specific program is manually selected untilautomatic program selection is activated again.

The processor 13 analyzes the observed user interaction in step 65, andan “undo a program change” command shortly after an automatic programchange has taken place is by the processor 13 interpreted as anerroneous program change. Therefor the processor 13 analyzes the form ofthe histogram calculated by the classifier 15—is there a significantpeak indicating that the auditory environment is homogeneous or are twoor more peaks indicating that the auditory environment is heterogeneous.A heterogeneous auditory environment can be interpreted as the auditoryenvironment being fluctuating or as the auditory environmenttransitioning from one audio type to another. Several different bins inthe histogram may lead to the selection of a specific program. If theprocessor 13 deems the auditory environment to be fluctuating, it startsanalyzing the individual values for the specific characteristics foreach sample. When the analysis carried out in step 65 shows that asignificant proportion of the values are close to one of the thresholdsshown in FIG. 6, and when the thresholds have not been modified recently(step 66), the processor 13 adjusts in step 69 the specific threshold sothe individual values for the specific characteristic will substantiallyfall in the interval pointing towards the program selected by the user.It is marked with a dotted arrow that the adaptive adjustment affectsthe monitoring of the auditory environment in step 60.

By adjusting the thresholds used by the classifier adaptively, theauditory environment will shift from being regarded as heterogeneoustowards being homogeneous. Hereby the risk of the program selector 16causing a programs change due to a misinterpretation of the auditoryenvironment is significantly reduced. After detecting a user interactionin step 64, evaluating the need for adaptively adjusting an appropriatethreshold in step 65, and actually changing the threshold in step 66 ifrequired, the processor 13 goes back to step 64 waiting for the nextuser interaction.

Preferably the adaptive adjustment of the thresholds is handled in thehearing aid 10 itself as explained above. However, as the personalcommunication device 20 may be a smartphone and therefor include aprocessor, too, the implementation of the invention may include that theprocessor 13 via the short range data connection transmits theindividual values for the specific characteristics for each sample andthe thresholds currently used to the personal communication device 20.Then the personal communication device 20 calculates an appropriate newset of thresholds—e.g. by ensuring that the individual values whenGauss-distributed has a significant proportion—e.g. at least 75% orpreferably above 90%—of the values in the appropriate interval or bin.

Preferably, the auxiliary classifier 24 uploads the new set ofthresholds to the remote server 40, together with the statistical datafrom the classifier 51, and an indication of user satisfaction. Usersatisfaction may be entered actively by a rating screen with e.g. a 1-5stars rating, or passively based on no further changes requested. Thesestatistical data from the classifier 51 may include the actual counts inthe histogram or the set of individual values for the specificcharacteristics for each audio sample. Preferably both are included. Theremote server 40 stores the uploaded data set in data storage 41. Theuploaded data is in a predefined format controlled by thedatabase/server operator and specified in the downloadable apps. Herebythe uploaded data set may be clustered with similar uploaded thresholds,and the data set is available for calculating future factory thresholdsettings for classifiers, and fixes or solution offerings for specificproblematic auditory environment. These solution offerings may includethreshold settings for the classifier dealing with a problematicauditory environment or settings for one of the sub-systems controlledby the program selector 16—e.g. the transposer where the downloadablesettings assist the hearing aid to suppress or emphasize certaincharacteristics in a problematic auditory environment.

According to an embodiment of the invention the processor 13 of hearingaid 10 manages the adjustments when a user interaction via the personalcommunication device 20 has indicated that the current performance isunsatisfying. In rare situations, the processor 13 is not able to adjustthe classifier thresholds in a way so the hearing aid user is satisfiedwith the performance, so when the auxiliary classifier 24 in step 66realizes that the threshold has been modified recently—e.g. the secondrequest made with a few minutes—the auxiliary classifier apps willprompt the user for downloading a fix for dealing with a problematicauditory environment in step 67, and if the user confirms, the personalcommunication device 20 uploads in step 68 a request for a solutionincluding the relevant history and the current settings to the remoteserver 40. The server analyzes the problem automatically—or assisted byan audiologist—and responds by sending the requested settings includingthe thresholds. Once the settings have been received, the personalcommunication device 20 transfers the settings to the hearing aid 10 instep 69 where the processor 13 stores the thresholds as if thethresholds had been calculated by the processor 13 itself and changesprogram in step 63 if the settings included a new designated program.

For a sequence of samples for an auditory environment beingsubstantially homogeneous, the samples will, when the specificcharacteristic is measured for the classification, assume exact valuesbeing distributed substantially according to the normal (or Gaussian)distribution. This is illustrated in FIG. 8 where the frequency (y-axis)is plotted as a function of the values for the specific characteristic(x-axis). The frequency of the exact values is shown as a curve 80, andthe distribution has a center of gravity or mean value, μ, marked as avalue 81.

The Gaussian distribution has the standard deviation, σ, and thevariance σ². The parameters are easily calculated based upon the actualvalue set, and may be used for characterizing the curve 80. For example,approximately 68% of the total number of exact values will fall in therange defined by the mean value, μ, +/− the standard deviation, σ. FIG.8 shows a threshold value 82 for the specific characteristic, and whenthe mean value, μ, of the audio samples for the auditory environmentfalls close to threshold value 82, there will be a risk that theclassifier 51 will toggle between the two intervals divided by thethreshold 82—even though the auditory environment is quite stable with asmall standard deviation σ. This may result in unintended programchanges.

When the analyzer 52 has detected that the auditory environment isheterogeneous, the processor 13 investigates the reason. If theprocessor 13 realized that the actual value set follows a Gaussiandistribution and that

-   -   the standard deviation, σ, is smaller than a predetermined        value—this predetermined value is small compared to the overall        range for the specific characteristic, less than e.g. 10% of the        overall range and preferably less than e.g. 5% of the overall        range, and that    -   the threshold 82 falls in a distance from the mean value, μ,        smaller than the standard deviation, σ;        then the processor 13 adjusts the threshold in the direction        indicated by the arrow to a new threshold value 83.

The threshold value adjustment may preferably be:

-   -   in fixed steps e.g. corresponding to the predetermined value to        which the standard deviation, σ, is compared,    -   the calculated standard deviation, σ, or    -   a value ensuring that the new, adjusted threshold is in a        distance from the mean value, μ, corresponding to the standard        deviation, σ.

Preferably the adjusted thresholds are maintained until the auditoryenvironment changes again, and hereafter the thresholds assume theoriginally set values. However the processer 13 may beneficiallyremember past amendments if the adjusted thresholds have been amended ina similar way several times.

EEG (Electroencephalography) is recording of electrical activity alongthe scalp, and the recordings may provide information about the brainactivity or the mental state of the person. EEG electrodes may beprovided integrally with the hearing aid (not shown)—e.g. inside the earcanal and/or on a hearing aid housing placed behind the ear. Based onthe EEG recording there may be provided a specific characteristicrepresentation of the hearing aid user's mood.

The adaptive classifier according to one aspect of the invention waswith reference to FIGS. 7 and 8 described for amending one threshold forone specific characteristic. However, according to a further aspect ofthe invention you may have multiple specific characteristics availablefor the program selector 16. These characteristics may includecharacteristics related to the audio signal, to the location of thehearing system (the hearing aid 10 and the personal communication 20),to the clock (actual time of the day), to the calendar of the personalcommunication 20, and to the mood of the hearing aid user (the EEGsignal).

An adaptive classifier for program selection in a hearing aid and basedupon multiple specific characteristics will operate in amulti-dimensional feature space. Such a multi-dimensional feature spaceis e.g. described by Woźniak and Krawczyk in “Combined classifier basedon feature space partitioning” in International Journal of AppliedMathematics and Computer Science. Volume 22, Issue 4, Pages 855-866.

FIG. 9 illustrates a two-dimensional feature space defined by the axis134 and 135 representing two of the specific characteristics. Based onuser feed-back, the two-dimensional feature space is divided bythresholds 130 and 132 into multiple decisions—here three—selectinghearing aid program #1, #2 or #3, respectively. When the classifierobserves that the specific characteristics values are changing in a wayso a new decision has to be made—for example that the coordinates forthe auditory environment moves from the areas in which hearing aidprogram #2 is selected to a position 133 where hearing aid program #3 isselected, then the program selector 16 selects hearing aid program #3.If the user changes back the hearing aid program to program #2 asexplained above, the processor identifies the change as an error andadapts the threshold curve 130 accordingly, and then future observationsfalling in the area between the threshold curve 130 and the curve 132will cause a decision to select the hearing aid program #2.

A multi-dimensional feature space based classifier is verycomputing-intensive and may require support for vector algorithms.However smartphones are nowadays pretty powerful and will be able tohandle such calculations. Hearing aid processors may in the future alsobecome able to handle such calculations.

The thresholds of a multi-dimensional feature space based classifier maybe set from factory during the manufacture, and is adapted to adapt thethresholds adaptively when user input is received. Hereby the thresholdswill over time mutate from the standard setting to a personalizedsetting based on the user experience and feed-back.

The invention claimed is:
 1. A hearing system including a hearing aidand a personal communication device, the hearing aid and the personalcommunication device being connectable via a wireless communication linksuch that the personal communication device provides a user interfacefor controlling a program selector component of the hearing aid bysending a program change command caused by user input, wherein: thehearing aid comprises a signal processor for processing and amplifyingsound to alleviate a hearing loss for a hearing-impaired individual, thesignal processor having a signal processing sub-system with at least twomodes of operation; the program selector component is adapted forautomatically selecting one of the at least two modes of operation forthe signal processing sub-system according to a statistical analysisperformed on at least one characteristic of an input signal, thestatistical analysis including comparison of said at least onecharacteristic to one or more thresholds; and the signal processor uponreception of the program change command adaptively adjusts at least oneof the one or more thresholds when the program change command followswithin a predetermined time after the automatic selection of the one ofthe at least two modes of operation.
 2. The hearing system according toclaim 1, wherein the automatic program selection in the hearing aid isbased upon multiple specific characteristics operating in amulti-dimensional feature space.
 3. The hearing system according toclaim 1, wherein the signal processing sub-system is selected from: adirectional microphone system configured to adaptively assume a polarpattern that produces the best signal-to-noise ratio in the currentlistening environment; a transposing sub-system for assisting the userto improve the speech perception, and an adaptive feedback cancellationsub-system analyzing the input signal, and in case the input signal isfound to include audible feedback whistling, reducing gain at theaffected frequency to provide a stable sound without feedback whistling.4. The hearing system according to claim 2, wherein themulti-dimensional feature space, in which the multiple specificcharacteristics operate, mutates adaptively over time from a standardsetting to a personalized setting based on user experience andfeed-back.
 5. The hearing aid system according to claim 1, furthercomprising EEG electrodes provided integrally with the hearing aid,wherein the input signal is derived from an EEG signal recorded by theEEG electrodes.
 6. A method of operating a hearing aid connected via awireless communication link to a personal communication device, thehearing aid having a signal processor for processing and amplifyingsound to alleviate a hearing loss for a hearing-impaired individual, thesignal processor having a signal processing sub-system with at least twomodes of operation, said method comprising steps of: automaticallyselecting one of the at least two modes of operation for the signalprocessing sub-system according to a statistical analysis of at leastone characteristic of an input signal, the statistical analysisincluding comparison of said at least one characteristic to one or morethresholds; providing, on the personal communication device whenconnected to the hearing aid, a user interface for controlling theprogram selector component of the hearing aid; sending, from thepersonal communication device, a program change command to the hearingaid caused by user input; and adaptively adjusting at least one of theone or more thresholds if the received program change command followswithin a predetermined time after the automatic selection of the one ofthe at least two modes of operation.
 7. A method according to claim 6,further comprising characterizing of the acoustic environment of thehearing aid during the statistical analysis.
 8. The method according toclaim 6, further comprising characterizing brain activity of the hearingaid user based on an EEG signal recorded by EEG electrodes providedintegrally with the hearing aid.
 9. A method according to claim 6,further comprising analyzing the multiple specific characteristics in amulti-dimensional feature space.
 10. A method according to claim 6,wherein the selection of the signal processing sub-system mode ofoperation comprises selection of one mode of a directional microphonesystem which can adaptively assume a polar pattern that produces thebest signal-to-noise ratio in the current listening environment.
 11. Amethod according to claim 6, wherein the selection of the signalprocessing sub-system mode of operation comprises selection of one modeof a transposing sub-system for assisting the user to improve speechperception.
 12. A method according to claim 6, wherein the selection ofthe signal processing sub-system mode of operation comprises selectionof one mode of an adaptive feedback cancellation sub-system analyzingthe input signal, and in case the input signal is found to includeaudible feedback whistling, reducing gain at the affected frequency toprovide a stable sound without feedback whistling.
 13. A methodaccording to claim 9, further comprising adaptively mutating themulti-dimensional feature space, in which the multiple specificcharacteristics operate, over time from a standard setting to apersonalized setting based on user experience and feed-back.
 14. Ahearing aid connectable to a personal communication device via awireless communication link, the personal communication device, whenconnected to the hearing aid, offers the user a user interface forcontrolling the hearing aid, said hearing aid comprising: a signalprocessor for processing and amplifying sound to alleviating a hearingloss for a hearing-impaired individual, the signal processor having asignal processing sub-system with at least two modes of operation; and aprogram selector component adapted for automatically selecting one ofthe at least two modes of operation for the signal processing sub-systemaccording to a statistical analysis performed on at least onecharacteristic of an input signal, the statistical analysis includingcomparison of said at least one characteristic to one or morethresholds; wherein the program selector component is configured toreceive a program change command from the personal communication devicevia the wireless communication link; wherein the signal processor uponreception of the program change command adaptively adjusts at least oneof the one or more thresholds, if the program change command followswithin a predetermined time after the automatic selection of the one ofthe at least two modes of operation.
 15. The hearing aid according toclaim 14, wherein the automatic program selection is based upon multiplespecific characteristics operating in a multi-dimensional feature space.16. The hearing aid according to claim 14, wherein the signal processingsub-system is selected from: a directional microphone system configuredto adaptively assume a polar pattern that produces a bestsignal-to-noise ratio in current listening environment; a transposingsub-system for assisting the user to improve speech perception, and anadaptive feedback cancellation sub-system analyzing the input signal,and in case the input signal is found to include audible feedbackwhistling, reducing gain at the affected frequency to provide a stablesound without feedback whistling.
 17. The hearing aid according to claim15, wherein the multi-dimensional feature space, in which the multiplespecific characteristics operate, mutates adaptively over time from astandard setting to a personalized setting based on user experience andfeed-back.
 18. The hearing aid according to claim 14, further comprisingintegrated EEG electrodes, and the input signal is derived from an EEGsignal recorded by the EEG electrodes.